However, few researchers have explored the patterns of misclassifications by current DNNs. For instance, Dodge et al. [1]} found that DNNs performance is much lower
than human performance on distorted images. Understanding these patterns is particularly important because it could guide us to design more robust DNNs that make fewer mistakes and generalize better.
